A general dual-bolus approach for quantitative DCE-MRI

Kershaw, Lucy; Cheng, Hai‐Ling Margaret

doi:10.1016/j.mri.2010.08.009

Cited by 41 publications

(38 citation statements)

References 18 publications

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“…One unique contribution of this study is the first demonstration of a dual bolus approach (17) to quantitative DCE-MRI within the kidney, a method previously employed in cardiac imaging. A key advantage of this approach is the decoupling of AIF and tissue uptake measurement, which allows the AIF to be sampled with a very high temporal resolution, yet accommodates high spatial resolution when imaging the tissue of interest.…”

Section: Discussionmentioning

confidence: 99%

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Quantification of renal perfusion: Comparison of arterial spin labeling and dynamic contrast‐enhanced MRI

Winter

Lawrence

Cheng

2011

Magnetic Resonance Imaging

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Purpose: To provide the first comparison of absolute renal perfusion obtained by arterial spin labeling (ASL) and separable compartment modeling of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI). Moreover, we provide the first application of the dual bolus approach to quantitative DCE-MRI perfusion measurements in the kidney. Materials and Methods:Consecutive ASL and DCE-MRI acquisitions were performed on six rabbits on a 1.5 T MRI system. Gadolinium (Gd)-DTPA was administered in two separate injections to decouple measurement of the arterial input function and tissue uptake curves. For DCE perfusion, pixel-wise and mean cortex region-of-interest tissue curves were fit to a separable compartment model. Results:Absolute renal cortex perfusion estimates obtained by DCE and ASL were in close agreement: 3.28 6 0.59 mL/g/min (ASL), 2.98 6 0.60 mL/g/min (DCE), and 3.57 6 0.96 mL/g/min (pixel-wise DCE). Renal medulla perfusion was 1.53 6 0.35 mL/g/min (ASL) but was not adequately described by the separable compartment model. Conclusion:ASL and DCE-MRI provided similar measures of absolute perfusion in the renal cortex, offering both noncontrast and contrast-based alternatives to improve current renal MRI assessment of kidney function.

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Section: Discussionmentioning

confidence: 99%

“…To account for small residual contrast from the prebolus, T 1 measurements of the kidney were made immediately prior to injection of the main bolus. The accuracy of this technique, specifically, the equivalence of DCE parameters obtained from a dual versus single bolus injection, has been investigated systematically (17).…”

Section: Discussionmentioning

confidence: 99%

Quantification of renal perfusion: Comparison of arterial spin labeling and dynamic contrast‐enhanced MRI

Winter

Lawrence

Cheng

2011

Magnetic Resonance Imaging

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“…Their experiments were performed on a 1.89 T scanner with temporal resolution of 0.9 s following a bolus injection of 0.3 mmol/kg gadodiamide, and the contrast media concentration vs. time in the aorta was estimated by a combination of arterial blood sampling and phase-sensitive imaging. Kershaw et al developed a dual-bolus technique, by splitting the contrast media dose of 0.2 mmol/kg into 20% for the pre-bolus and 80% for the main bolus, for quantitative DCE-MRI of rabbit aorta at 1.5 T [12]. They demonstrated that the AIF can be reliably measured following a low-dose pre-bolus with 0.44 s temporal resolution (using a TRICKS sequence [13]), giving the same curve as an AIF measured in the conventional way following a high-dose bolus with temporal resolution of 1.3 s. However, routine clinical DCE-MRI scans of the prostate are generally obtained at much lower temporal resolution (e.g.…”

Section: Introductionmentioning

confidence: 99%

Arterial input functions (AIFs) measured directly from arteries with low and standard doses of contrast agent, and AIFs derived from reference tissues

Wang

Fan

Medved

et al. 2016

Magnetic Resonance Imaging

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Measurements of arterial input function (AIF) can have large systematic errors at standard contrast agent doses in dynamic contrast enhanced MRI (DCE-MRI). We compared measured AIFs from low dose (AIFLD) and standard dose (AIFSD) contrast agent injections, as well as the AIF derived from a muscle reference tissue and artery (AIFref). Twenty-two prostate cancer patients underwent DCE-MRI. Data were acquired on a 3 T scanner using an mDixon sequence. Gadobenate dimeglumine was injected twice, at doses of 0.015 and 0.085 mmol/kg. Directly measured AIFs were fitted with empirical mathematical models (EMMs) and compared to the AIF derived from a muscle reference tissue (AIFref). EMMs accurately fitted the AIFs. The 1st and 2nd pass peaks were visualized in AIFLD, but not in AIFSD, thus the peak and shape of AIFSD could not be accurately measured directly. The average scaling factor between AIFSD and AIFLD in the washout phase was only 56% of the contrast dose ratio (~6:1). The shape and magnitude of AIFref closely approximated that of AIFLD after empirically determined dose-dependent normalization. This suggests that AIFref may be a good approximation of the local AIF.

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“…The typical analysis strategy is to fit a model function to the first bolus passage (Benner et al, 1997;Kershaw and Cheng, 2011;Kim et al, 2010). To this end, optimization techniques such as independent component analysis and iterative algorithms (Gruner and Taxt, 2006) have been developed.…”

Section: Introductionmentioning

confidence: 99%

Robust Quantification of Microvascular Transit Times via Linear Dynamical Systems using Two-Photon Fluorescence Microscopy Data

Chinta

Lindvere

Stefanović

2012

J Cereb Blood Flow Metab

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Vascular transit time is an important indicator of microcirculatory health. We present a secondorder-plus-dead-time (SOPDT) model for robust estimation of kinetic parameters characterizing microvascular bolus passage using two-photon fluorescence microscopy (2PFM) in anesthetized rats receiving somatosensory stimulation. This methodology enables quantification of transit time, time-to-peak, overshoot, and rate of bolus passage through the microvascular network. The overall transit time during stimulation, of 2.2±0.1 seconds, was shorter (PB0.0008) than that at rest (2.7 ± 0.2 seconds). When compared with conventional c-variate modeling, the SOPDT modeling yielded better quality of fit both at rest (P < 0.0001) and on activation (P < 0.001).

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A general dual-bolus approach for quantitative DCE-MRI

Cited by 41 publications

References 18 publications

Quantification of renal perfusion: Comparison of arterial spin labeling and dynamic contrast‐enhanced MRI

Quantification of renal perfusion: Comparison of arterial spin labeling and dynamic contrast‐enhanced MRI

Arterial input functions (AIFs) measured directly from arteries with low and standard doses of contrast agent, and AIFs derived from reference tissues

Robust Quantification of Microvascular Transit Times via Linear Dynamical Systems using Two-Photon Fluorescence Microscopy Data

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